Hybrid machine learning system for integrated yield management in semiconductor manufacturing

摘要

Yield is one of the most important indices determining the success in semiconductor manufacturing business. Previous yield management efforts are to enhance yield of the specific process through the use of statistical and experimental analysis, but they fail to manage the yields of overall manufacturing processes.This research provides a framework for implementing such an integrated yield management system, which uses inductive decision trees and neural networks with a back propagation algorithm and a self-organizing mapping algorithm to manage yields over major manufacturing processes.